1 /* PSPP - a program for statistical analysis.
2 Copyright (C) 2006, 2009 Free Software Foundation, Inc.
4 This program is free software: you can redistribute it and/or modify
5 it under the terms of the GNU General Public License as published by
6 the Free Software Foundation, either version 3 of the License, or
7 (at your option) any later version.
9 This program is distributed in the hope that it will be useful,
10 but WITHOUT ANY WARRANTY; without even the implied warranty of
11 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12 GNU General Public License for more details.
14 You should have received a copy of the GNU General Public License
15 along with this program. If not, see <http://www.gnu.org/licenses/>. */
18 #include <libpspp/compiler.h>
19 #include <output/table.h>
21 #include <data/case.h>
22 #include <data/casereader.h>
23 #include <data/dictionary.h>
24 #include <data/procedure.h>
25 #include <data/variable.h>
26 #include <data/value.h>
27 #include <data/value-labels.h>
29 #include <libpspp/message.h>
30 #include <libpspp/assertion.h>
38 #define _(msgid) gettext (msgid)
40 #include <libpspp/misc.h>
42 #include <gsl/gsl_cdf.h>
43 #include <gsl/gsl_randist.h>
47 #include <libpspp/hash.h>
49 static double calculate_binomial_internal (double n1, double n2,
54 swap (double *i1, double *i2)
62 calculate_binomial (double n1, double n2, double p)
64 const double n = n1 + n2;
65 const bool test_reversed = (n1 / n > p ) ;
72 return calculate_binomial_internal (n1, n2, p);
76 calculate_binomial_internal (double n1, double n2, double p)
78 /* SPSS Statistical Algorithms has completely different and WRONG
81 double sig1tailed = gsl_cdf_binomial_P (n1, p, n1 + n2);
84 return sig1tailed > 0.5 ? 1.0 :sig1tailed * 2.0;
90 do_binomial (const struct dictionary *dict,
91 struct casereader *input,
92 const struct binomial_test *bst,
93 struct freq_mutable *cat1,
94 struct freq_mutable *cat2,
100 const struct one_sample_test *ost = (const struct one_sample_test *) bst;
103 while ((c = casereader_read(input)) != NULL)
106 double w = dict_get_case_weight (dict, c, &warn);
108 for (v = 0 ; v < ost->n_vars ; ++v )
110 const struct variable *var = ost->vars[v];
111 const union value *value = case_data (c, var);
112 int width = var_get_width (var);
114 if (var_is_value_missing (var, value, exclude))
117 if ( NULL == cat1[v].value )
119 cat1[v].value = value_dup (value, width);
122 else if ( 0 == compare_values_short (cat1[v].value, value, var))
124 else if ( NULL == cat2[v].value )
126 cat2[v].value = value_dup (value, width);
129 else if ( 0 == compare_values_short (cat2[v].value, value, var))
131 else if ( bst->category1 == SYSMIS)
132 msg (ME, _("Variable %s is not dichotomous"), var_get_name (var));
137 return casereader_destroy (input);
143 binomial_execute (const struct dataset *ds,
144 struct casereader *input,
145 enum mv_class exclude,
146 const struct npar_test *test,
151 const struct binomial_test *bst = (const struct binomial_test *) test;
152 const struct one_sample_test *ost = (const struct one_sample_test*) test;
154 struct freq_mutable *cat1 = xzalloc (sizeof (*cat1) * ost->n_vars);
155 struct freq_mutable *cat2 = xzalloc (sizeof (*cat1) * ost->n_vars);
157 assert ((bst->category1 == SYSMIS) == (bst->category2 == SYSMIS) );
159 if ( bst->category1 != SYSMIS )
163 v.f = bst->category1;
164 for (i = 0; i < ost->n_vars; i++)
165 cat1[i].value = value_dup (&v, 0);
168 if ( bst->category2 != SYSMIS )
172 v.f = bst->category2;
173 for (i = 0; i < ost->n_vars; i++)
174 cat2[i].value = value_dup (&v, 0);
177 if (do_binomial (dataset_dict(ds), input, bst, cat1, cat2, exclude))
179 struct tab_table *table = tab_create (7, ost->n_vars * 3 + 1, 0);
181 tab_dim (table, tab_natural_dimensions);
183 tab_title (table, _("Binomial Test"));
185 tab_headers (table, 2, 0, 1, 0);
187 tab_box (table, TAL_1, TAL_1, -1, TAL_1,
188 0, 0, table->nc - 1, tab_nr(table) - 1 );
190 for (v = 0 ; v < ost->n_vars; ++v)
193 struct string catstr1;
194 struct string catstr2;
195 const struct variable *var = ost->vars[v];
197 ds_init_empty (&catstr1);
198 ds_init_empty (&catstr2);
200 var_append_value_name (var, cat1[v].value, &catstr1);
201 var_append_value_name (var, cat2[v].value, &catstr2);
203 tab_hline (table, TAL_1, 0, tab_nc (table) -1, 1 + v * 3);
206 tab_text (table, 0, 1 + v * 3, TAB_LEFT, var_to_string (var));
207 tab_text (table, 1, 1 + v * 3, TAB_LEFT, _("Group1"));
208 tab_text (table, 1, 2 + v * 3, TAB_LEFT, _("Group2"));
209 tab_text (table, 1, 3 + v * 3, TAB_LEFT, _("Total"));
212 tab_float (table, 5, 1 + v * 3, TAB_NONE, bst->p, 8, 3);
214 /* Category labels */
215 tab_text (table, 2, 1 + v * 3, TAB_NONE, ds_cstr (&catstr1));
216 tab_text (table, 2, 2 + v * 3, TAB_NONE, ds_cstr (&catstr2));
219 tab_float (table, 3, 1 + v * 3, TAB_NONE, cat1[v].count, 8, 0);
220 tab_float (table, 3, 2 + v * 3, TAB_NONE, cat2[v].count, 8, 0);
222 n_total = cat1[v].count + cat2[v].count;
223 tab_float (table, 3, 3 + v * 3, TAB_NONE, n_total, 8, 0);
225 /* Observed Proportions */
226 tab_float (table, 4, 1 + v * 3, TAB_NONE,
227 cat1[v].count / n_total, 8, 3);
228 tab_float (table, 4, 2 + v * 3, TAB_NONE,
229 cat2[v].count / n_total, 8, 3);
230 tab_float (table, 4, 3 + v * 3, TAB_NONE,
231 (cat1[v].count + cat2[v].count) / n_total, 8, 2);
234 sig = calculate_binomial (cat1[v].count, cat2[v].count, bst->p);
235 tab_float (table, 6, 1 + v * 3, TAB_NONE, sig, 8, 3);
237 ds_destroy (&catstr1);
238 ds_destroy (&catstr2);
241 tab_text (table, 2, 0, TAB_CENTER, _("Category"));
242 tab_text (table, 3, 0, TAB_CENTER, _("N"));
243 tab_text (table, 4, 0, TAB_CENTER, _("Observed Prop."));
244 tab_text (table, 5, 0, TAB_CENTER, _("Test Prop."));
246 tab_text (table, 6, 0, TAB_CENTER | TAT_PRINTF,
247 _("Exact Sig. (%d-tailed)"),
248 bst->p == 0.5 ? 2: 1);
250 tab_vline (table, TAL_2, 2, 0, tab_nr (table) -1);
254 for (v = 0; v < ost->n_vars; v++)
256 free (cat1[v].value);
257 free (cat2[v].value);